Smart Edge Computing E-Book
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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
This book pioneers the synergy between state-of-the-art edge computing technologies and the power of operations research. It comprehensively explores real-world applications, demonstrating how various operations' research techniques enhance edge computing's efficiency, reliability and resource allocation. Innovative solutions for dynamic task scheduling, load balancing and data management, all tailored to the unique challenges of edge environments, are displayed. Starting with operation research methodologies with foundations, applications and research challenges in edge computing and an overview of digital education, this book continues with an exploration of applications in the health sector using IoT, intelligent payment procedures and performance measurement of edge computing, using edge computing and operation research. Smart or AI-based applications are also explored further on and the book ends with insight into ultralightweight and security protocols with solutions for IoT using blockchain.
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Seitenzahl: 388
Veröffentlichungsjahr: 2024
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Table of Contents
Cover
Table of Contents
Dedication Page
Title Page
Copyright Page
Preface
Acknowledgments
1 Introduction to Operations Research Methodologies
1.1. Introduction
1.2. Decision-making framework/models for operations research
1.3. Operations research in IoT, IIoT, edge and smart edge computing, sensor data
1.4. Paradigms and procedures
1.5. Conclusion
1.6. References
2 Edge Computing: The Foundation, Emergence and Growing Applications
2.1. Introduction
2.2. Objective of the work
2.3. Methods adopted
2.4. Edge computing and edge cloud: basics
2.5. Edge computing and edge devices
2.6. Edge computing: working fashions, buying and deploying and 5G
2.7. Functions and features of edge computing
2.8. Edge computing: applications and examples
2.9. Drawbacks, obstacles and issues in edge computing
2.10. Edge computing, cloud computing and Internet of Things: some concerns
2.11. Future and emergence of edge computing
2.12. Conclusion
2.13. Acknowledgment
2.14. References
3 Utilization of Edge Computing in Digital Education: A Conceptual Overview
3.1. Introduction
3.2. Objectives
3.3. Methodology used
3.4. Digital education
3.5. Education and information science
3.6. Edge computing
3.7. Conclusion
3.8. Acknowledgment
3.9. References
4 Edge Computing with Operations Research Using IoT Devices in Healthcare: Concepts, Tools, Techniques and Use Cases
4.1. Overview
4.2. The smartness of edge across artificial intelligence with the IoT
4.3. Promising approaches in edge healthcare system
4.4. Impact of smartphones on edge computing
4.5. Tools, techniques and use cases
4.6. Significant forthcomings of edge healthcare IoT
4.7. Software and hardware companies developing healthcare tools
4.8. Summary
4.9. References
5 Performance Measures in Edge Computing Using the Queuing Model
5.1. Introduction
5.2. Methodology
5.3. Conclusion
5.4. Future scope
5.5. References
6 A Smart Payment Transaction Procedure by Smart Edge Computing
6.1. Introduction
6.2. Related works
6.3. Ethereum
6.4. Ethereum’s components
6.5. General-purpose blockchains to decentralized applications (DApps)
6.6. Ether currency units
6.7. Ethereum wallet
6.8. A simple contract: a test Ether faucet
6.9. Ethereum clients
6.10. Conclusion
6.11. References
7 Statistical Learning Approach for the Detection of Abnormalities in Cancer Cells for Finding Indication of Metastasis
7.1. Introduction
7.2. Edge computation: a new era
7.3. Impact of edge computation in cancer treatment
7.4. Assessment parameters operational methodologies
7.5. Shape descriptor analysis: statistical approach
7.6. Results and discussion
7.7. Conclusion
7.8. References
8 Overcoming the Stigma of Alzheimer’s Disease by Means of Natural Language Processing as well as Blockchain Technologies
8.1. Introduction
8.2. Alzheimer’s disease
8.3. Alzheimer’s disease types
8.4. NLP in chat-bots/AI companions
8.5. Proposed methodologies for reduction of stigma
8.6. Blockchain technology for securing all medical data
8.7. Conclusion
8.8. Future scope
8.9. Acknowledgments
8.10. References
9 Computer Vision-based Edge Computing System to Detect Health Informatics for Oral Pre-Cancer
9.1. Introduction
9.2. Related works
9.3. Materials and methods
9.4. Results
9.5. Conclusion
9.6. References
10 A Study of Ultra-lightweight Ciphers and Security Protocol for Edge Computing
10.1. Introduction
10.2. Ultra-lightweight ciphers
10.3. Ultra-lightweight security protocols
10.4. Conclusion
10.5. References
11 A Study on Security Protocols, Threats and Probable Solutions for Internet of Things Using Blockchain
11.1. Introduction
11.2. IoT architecture and security challenges
11.3. Security threat classifications
11.4. Security solutions for IoT
11.5. Blockchain-based IoT paradigm: security and privacy issues
11.6. IoT Messaging Protocols
11.7. Advantages of edge computing
11.8. Conclusion
11.9. References
List of Authors
Index
Other titles from ISTE in Computer Engineering
End User License Agreement
List of Tables
Chapter 1
Table 1.1. Global optimization taxonomy history
Table 1.2. Criterion of the algorithm selection
Chapter 2
Table 2.1. Different types of computing in contrast to edge computing
Chapter 4
Table 4.1. Breakdown of the AI technologies supporting edge computing-based re...
Table 4.2. Summary of various methods used in medical devices
Table 4.3. A collection of edge computing-based medical products with their we...
Chapter 5
Table 5.1. Comparison of resource utilization and delay in edge computing usin...
Chapter 7
Table 7.1. List of circularity values of basic shapes
Chapter 9
Table 9.1. Summary of cancer and pre-cancer detection techniques
Chapter 10
Table 10.1. Comparative study of ultra-lightweight ciphers
Table 10.2. Comparison between LEAP, MIFARE and RFB protocols
Table 10.3. Comparative study between MIFARE Ultralight C and Ultralight EV1
Table 10.4. Published versions of the RFB protocol
Chapter 11
Table 11.1. Comparisons between message protocols
List of Illustrations
Chapter 1
Figure 1.1. Objective function layers in surrogate optimization
Figure 1.2. Requests to the cloud
Figure 1.3. Queuing model for scheduler load optimization
Figure 1.4. Queuing model for scheduling optimization
Chapter 2
Figure 2.1. Basic characteristics of edge computing.
Figure 2.2. Ample benefits are possible from edge computing.
Figure 2.3. Emerging and most used areas of edge systems.
Figure 2.4. Depicted simple edge to cloud architecture layers.
Figure 2.5. Some of the challenges of edge computing and similar systems
Chapter 3
Figure 3.1. Concept of education and information science.
Figure 3.2. Conceptual diagram of edge computing in education.
Figure 3.3. Communication between different layers of edge computing in educat...
Figure 3.4. Stakeholders of edge computing in digital education
Figure 3.5. Advantages of edge computing in digital education
Chapter 4
Figure 4.1. Basic architecture of edge computing.
Figure 4.2. Merits and demerits of Big Data
Figure 4.3. An architecture of mobile edge computing
Figure 4.4. Deep feature extraction and model building for healthcare.
Figure 4.5. Smart healthcare software for medical practice
Figure 4.6. Architecture of high data reduction through cloud environment in h...
Figure 4.7. List of future edge healthcare and healthcare IoTs.
Chapter 5
Figure 5.1. “Cloud computing”architecture
Figure 5.2. Architecture of the edge–cloud system.
Figure 5.3. Edge model using queuing theory
Figure 5.4. Single server queuing model
Figure 5.5. Queuing model for edge computing.
Figure 5.6. Poisson’s distribution for the arrival process for the M/M/1 queui...
Figure 5.7. Calculation of the service waiting time (delay) using the M/M/1 qu...
Figure 5.8. Poisson’s distribution for the arrival process for the M/M/C queui...
Figure 5.9. Calculation of the service waiting time (delay)using the M/M/C que...
Figure 5.10. Poisson’s distribution for the arrival process for the M/M/C queu...
Figure 5.11. Calculation of the service waiting time (delay) using the M/M/C q...
Figure 5.12. Comparison between resource utilization and delay in edge computi...
Chapter 7
Figure 7.1. Block diagram of edge computation
Figure 7.2. List of circularity values of the alphabet dataset (A–C)
Figure 7.3. List of circularity values of the alphabet dataset (D–F)
Figure 7.4. List of circularity values of the alphabet dataset (G–K)
Figure 7.5. Circularity value measurement of cancerous cells using a software ...
Chapter 8
Figure 8.1. Iconic model for the treatment of Alzheimer’s patients.
Figure 8.2. A synopsis of possible NLP methodology.
Figure 8.3. Structure of the blockchain
Figure 8.4. Graphical illustration of a hypothetical architecture in which the...
Figure 8.5. Blockchain-based applications are used to secure medical data by i...
Chapter 9
Figure 9.1. Cancerous cells.
Figure 9.2. Non-cancerous cells.
Figure 9.3. Application screenshot of cancerous and non-cancerous cells.
Figure 9.4. RGB color segmentation analysis of cancerous and non-cancerous cel...
Figure 9.5. Red color segmentation analysis of cancerous and non-cancerous cel...
Figure 9.6. Color segmentation analysis of cancerous and non-cancerous cells.
Chapter 10
Figure 10.1. SLIM encryption
Figure 10.2. Substitution layer
Figure 10.3. Permutation layer
Figure 10.4. Encryption function
Figure 10.5. Round permutation
Figure 10.6. F-function
Figure 10.7. S-box
Figure 10.8. Initialization process
Figure 10.9. Encryption process
Figure 10.10. Decryption process
Figure 10.11. Ideal case scenario for LEAP protocol
Figure 10.12. Compromised sensor node scenario for LEAP protocol
Figure 10.13. MIFARE Ultralight AES IC
Figure 10.14. Working structure of RFB protocol
Guide
Cover Page
Table of Contents
Dedication Page
Title Page
Copyright Page
Preface
Acknowledgments
Begin Reading
List of Authors
Index
Other titles from ISTE in Computer Engineering
WILEY END USER LICENSE AGREEMENT
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The editors would like to dedicate this book to their parents,life partners, children, students, scholars, friends and colleagues
International Perspectives in Decision Analytics and Operations Research Set
coordinated by
Prasenjit Chatterjee
Volume 2
Smart Edge Computing
An Operation Research Perspective
Edited by
Aline Courie-Lemeur
Anupam Ghosh
Jyotsna Kumar Mandal
Tanupriya Choudhury
Prasenjit Chatterjee
First published 2024 in Great Britain and the United States by ISTE Ltd and John Wiley & Sons, Inc.
Apart from any fair dealing for the purposes of research or private study, or criticism or review, as permitted under the Copyright, Designs and Patents Act 1988, this publication may only be reproduced, stored or transmitted, in any form or by any means, with the prior permission in writing of the publishers, or in the case of reprographic reproduction in accordance with the terms and licenses issued by the CLA. Enquiries concerning reproduction outside these terms should be sent to the publishers at the undermentioned address:
ISTE Ltd27-37 St George’s RoadLondon SW19 4EUUKwww.iste.co.uk
John Wiley & Sons, Inc.111 River StreetHoboken, NJ 07030USAwww.wiley.com
© ISTE Ltd 2024The rights of Rajdeep Chakraborty, Anupam Ghosh, Jyotsna Kumar Mandal, Tanupriya Choudhury and Prasenjit Chatterjee to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988.
Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s), contributor(s) or editor(s) and do not necessarily reflect the views of ISTE Group.
Library of Congress Control Number: 2023944978
British Library Cataloguing-in-Publication DataA CIP record for this book is available from the British LibraryISBN 978-1-78630-863-4
Preface
Smart edge computing, from an operations research perspective, is a cutting-edge paradigm that integrates computational intelligence, data analytics and network technologies to optimize and enhance the efficiency of edge devices and networks. In this context, operations research plays a crucial role in addressing complex challenges related to resource allocation, task scheduling and decision-making at the edge of the network. By leveraging mathematical models, algorithms and optimization techniques, operations research enables the efficient distribution of computational tasks and data processing among edge devices, minimizing latency, conserving energy and ensuring seamless real-time data processing. Moreover, this approach empowers the deployment of artificial intelligence and machine learning algorithms at the edge, enabling intelligent devices to make autonomous decisions and adapt to dynamic environments. Smart edge computing, underpinned by operations research principles, is poised to revolutionize industries by unlocking the full potential of the Internet of Things (IoT), enhancing mobile computing and fostering the development of smart cities and autonomous systems with unprecedented efficiency and agility. This book is organized into 11 chapters, which are summarized as follows.
Chapter 1 discusses the domain of operational research and its various techniques used for complex problem-solving and decision-making. It also explores mathematical models and cutting-edge approaches for quantitative research, yielding both theoretically sound and practically applicable insights. The main objective of this chapter is to introduce the use of operations research methods in scientific decision-making, design, analysis and management, providing a practical guide to their applications in the context of edge computing.
Chapter 2 provides an overview of edge computing, its functions and applications in various fields, including automated vehicle management, logistics and smart cities.
Chapter 3 discusses how edge computing promotes education and information science, providing a conceptual overview and communication between different layers in digital education using diagrams. It enhances system reliability and scalability. Edge computing is a technology that leverages the massive data generated by IoT devices through distributed computing. It reduces data traffic by sending only relevant data across the network. In healthcare, edge computing combined with the IoT has led to significant digital advancements, enabling remote patient monitoring and various medical applications.
Chapter 4 provides a systematic review of edge computing’s reputation in healthcare and its potential to address challenges and open up new opportunities for researchers. Edge computing, along with deep learning, is considered the future of digital products and can have a significant impact on society by solving tasks efficiently.
Chapter 5 applies queueing models to edge computing and analyzes the performance of edge-cloud computing. Performance analysis shows that increasing the number of edge servers reduces waiting time and resource utilization.
Chapter 6 discusses the promising field of smart edge computing and its potential dependency on IoT devices for computationally intensive tasks. It highlights the importance of blockchain-based technologies, especially for tracking and managing transactions. Ethereum’s value proposition for decentralized applications is explored, with a focus on smart contracts and their various applications.
Chapter 7 explores the application of operational research and statistical learning in the analysis of cancer progression. It introduces an invariant shape descriptor methodology using geodesic and z-transformations of carcinoma images.
Chapter 8 discusses the burden of chronic diseases, focusing on Alzheimer’s disease (AD) as a challenging neurodegenerative disease. The use of AI (Artificial Intelligence) and NLP (Natural Language Processing) is explored to analyze public perceptions of AD through social media. Concerns about unreliable medical records and data security are highlighted, and the potential of blockchain-based methods for data control is suggested.
Chapter 9 discusses the significance of the IoT in various industries and its role in automation for the Industrial IoT. It focuses on assessing the clinical correlation between histological changes in the pre-cancerous tissues of subjects with oral submucous fibrosis and the normal control group using histochemical analysis.
Chapter 10 discusses the importance of security protocols for Internet information transmission, and explores the concepts of lightweight and ultra-lightweight protocols.
Chapter 11 discusses the importance of security in the IoT environment and the need to address security issues at different levels. It highlights the use of lightweight cryptography algorithms to secure IoT devices in various applications.
Dr. Rajdeep CHAKRABORTY
October 2023
Acknowledgments
The editors wish to express their warm thanks and deep appreciation to those who provided input, support, constructive suggestions and comments, and assisted in the editing and proofreading of this book.
This book would not have been possible without the valuable scholarly contributions of authors across the globe.
The editors would like to thank their family members and friends for their endless support and motivation.
They are very grateful to all the members who contributed to the editorial and review process of this book.
Mere words cannot express the editors’ deep gratitude to the entire ISTE publishing team for keeping faith and showing the right path to accomplish this very timely book.
Finally, the editors take this opportunity to thank all the readers and expect that this book will continue to inspire and guide them in their future endeavors.
The editors
